Analytic number theorists usually seek to show that sequences which appear naturally in arithmetic are “well-distributed” in some appropriate sense. In various discrepancy problems, combinatorics researchers have analyzed limitations to equi-distribution, as have Fourier analysts when working with the “uncertainty principle”. In this article we find that these ideas have a natural setting in th...

Each disaster presents itself with a unique set of characteristics that are hard to determine a priori. Using combinations of qualitative and quantitative methods, we develop the dimensions and their corresponding measures of the dynamic characteristics of disaster management tasks and test the relationships between the various dimensions of task uncertainty and knowledge sharing purposes. We c...

Introduction Conclusions References

We derive an optimal entropic uncertainty relation for an arbitrary pair of observables in a two-dimensional Hilbert space. Such a result, for the simple case we are considering, definitively improves all the entropic uncertainty relations which have appeared in the literature.

Bayesian Uncertainty Quantification for Subsurface Inversion Using a Multiscale Hierarchical Model Anirban Mondal, Bani Mallick, Yalchin Efendiev & Akhil Datta-Gupta a Department of Statistics, Texas A&M University, College Station, TX 77843 (; ) b Department of Mathematics, Texas A&M University, College Station, TX 77843 () c Petroleum Engineering Department, Texas A&M University, College Stat...

Article history: Received 2 August 2013 Received in revised form 6 November 2013 Accepted 2 December 2013 Available online 1 January 2014

the aim of this paper is to prove new quantitative uncertainty principle for the generalized fourier transform connected with a dunkl type operator on the real line. more precisely we prove an lp-lq-version of morgan's theorem.